International Journal of Analysis and Applications | 2026
Authors: Wanishsakpong W.; Kirtsaeng S.; Chinram R.; Panityakul T.
DOI: 10.28924/2291-8639-24-2026-5
Journal: International Journal of Analysis and Applications
Year: 2026
Publisher: Etamaths Publishing
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
The Yom river basin in one of the 22 main river basins of Thailand. This experiences perennial floods and droughts that heavily impact the agricultural sector. In order to reduce the impact, water management, including water level estimation. A considerable task of management is the quantitative forecasting of water levels. This study proposes appropriate forecasting models for time series of daily water level data from four water level measurement stations. The study period is from 2007 to 2022 on September. The efficiency of this forecasting model was determined from comparisons to three approaches, centered moving average model (CMA), additive decomposition model (DEC), Holt’s Winter additive model (WIN). Results indicated that: The forecasts of two years gave similar forecast patterns to the previously observed values. Mainly, (decomposition) was more accurate than the other approaches for all stations. The RMSEs of upstream was slightly greater than the downstream RMSEs for three approaches. © 2026 the author(s).
data restructuring; forecasting; high fluctuation basin